Although there is a good body of theoretical research to build new understanding, questions in aging research remain increasingly complex, intricate, and diverse. Comprehensive understanding of these pathways requires a broad integrative framework that addresses (a) the need for reliable and theory-driven measures of health and well-being, (b) the need for conceptual and empirical formulations of life challenges, (c) the need for study designs that link information at different levels of analysis, (d) the need for innovative statistical methodologies that are sensitive to complex dynamic changes, and (e) the need for strategies that integrate quantitative and qualitative sources of data. The proposed research is designed to collect such data through three mechanisms: (1) survey data-five waves collected on a yearly basis (collected on 300 subjects); (2) "data bursts"-daily diary data collected three times for a 56-day period (years 1, 3, and 5 on 300 subjects); and, (3) life story interview data collected twice (years 2 and 4) on 25 of the participants. Modeling processes of intraindividual variability and change can help to (a) reveal how long-term trajectories of gains and losses that are reasonably consistent across different individuals may differ dramatically within individuals (Aim 1); (b) elucidate how these complex trajectories of intraindividual changes are contoured by selective individual differences variables (Aim 2); (c) separate intraindividual differences in developmental growth from aspects of temporal phenomena that exhibit shorter-term variability over time (Aim 3); (d) demonstrate how dimensions of interindividual differences may be used to explain important, adaptive intraindividual processes (Aim 4); and (e) clarify, through the use of life stories (Aim 5), how individual development is embedded in multiple contexts (e.g., biological, familial, historical, social, and cultural). The results of the proposed research will provide an integrated model of resilience and well being in later life that will help inform intervention efforts to extend disability-free years to larger segments of the population.